Do Trading Mechanisms Affect Stylized Facts in Financial Markets? An Agent-based Simulation

An information-based multiasset artificial stock market characterized by different types of stocks and populated by heterogeneous agents is presented and studied so as to determine the influences of agents’ networks on the market’s structure. Agents are organized in networks that are responsible for the formation of the sentiments of the agents. In the market, agents trade risky assets in exchange for cash and share their sentiments by means of interactions that are determined by sparsely connected graphs. A central market maker (clearing house mechanism) determines the price process for each stock at the intersection of the demand and the supply curves. A set of market’s structure indicators based on the main single-assets and multiassets stylized facts have been defined, in order to study the effects of the agents’ networks. Results point out an intrinsic structural resilience of the stock market. In fact, the network is necessary in order to archive the ability to reproduce the main stylized facts, but also the market has some characteristics that are independent from the network and depend on the finiteness of traders’ wealth.

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Disposition effect and multi-asset market dynamics

Review of Behavioral Finance ◽

10.1108/rbf-01-2018-0003 ◽

2019 ◽

Vol 11 (2) ◽

pp. 144-164

Author(s):

Heba M. Ezzat

Keyword(s):

Asset Pricing ◽

Financial Markets ◽

Switching Behavior ◽

Asset Markets ◽

Disposition Effect ◽

Stylized Facts ◽

Content Type ◽

Agent Based ◽

Multiple Assets ◽

Pricing Dynamics

Purpose Asset pricing dynamics in a multi-asset framework when investors’ trading exhibits the disposition effect is studied. The purpose of this paper is to explore asset pricing dynamics and the switching behavior among multiple assets. Design/methodology/approach The dynamics of complex financial markets can be best explored by following agent-based modeling approach. The artificial financial market is populated with traders following two heterogeneous trading strategies: the technical and the fundamental trading rules. By simulation, the switching behavior among multiple assets is investigated. Findings The proposed framework can explain important stylized facts in financial time series, such as random walk price dynamics, bubbles and crashes, fat-tailed return distributions, absence of autocorrelation in raw returns, persistent long memory of volatility, excess volatility, volatility clustering and power-law tails. In addition, asset returns possess fractal structure and self-similarity features; though the switching behavior is only allowed among the asset markets. Practical implications The model demonstrates stylized facts of most real financial markets. Thereafter, the proposed model can serve as a testbed for policy makers, scholars and investors. Originality/value To the best of knowledge, no research has been conducted to introduce the disposition effect to a multi-asset agent-based model.

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Multi-agent modeling and simulation of a stock market

Investment Management and Financial Innovations ◽

10.21511/imfi.15(4).2018.10 ◽

2018 ◽

Vol 15 (4) ◽

pp. 123-134 ◽

Cited By ~ 1

Author(s):

Mohamed Amine Souissi ◽

Khalid Bensaid ◽

Rachid Ellaia

Keyword(s):

Decision Making ◽

Stock Market ◽

Financial Markets ◽

Modeling And Simulation ◽

Decision Making Process ◽

Agent Based Simulation ◽

Exogenous Variables ◽

Agent Based ◽

Agent Platforms ◽

Multi Agent

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

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